The cryptocurrency market has entered an era of stagnant growth. With retail traders either exiting or going dormant, trading volumes have plummeted, and the once-volatile market now barely stirs. Yet, amid this calm, quantitative trading continues to thrive—quietly, persistently, and with growing sophistication.
While many chase quick gains, a different breed of trader is leveraging algorithms, statistical models, and high-frequency strategies to generate consistent returns. To uncover the truth behind the hype, we spoke with nearly 20 teams claiming to specialize in crypto quant trading. Some have been in the game since 2013; most joined during the 2017 bull run. What emerged is a landscape defined by opportunity, risk, and a sharp divide between genuine expertise and misleading promises.
The New Gold Rush: Believers, Opportunists, and Pretenders
In the world of crypto quantitative trading, three distinct groups coexist: the true believers, the skilled opportunists, and the outright pretenders.
True believers like Pcoin founder Yin Hongliang have weathered multiple market cycles since 2013. Surviving Mt. Gox’s collapse, BitVC liquidations, and other black swan events, these long-term players evolved from basic arbitrage—commonly known as “brick moving” across exchanges—to advanced strategies including futures-spot (basis), inter-exchange futures, triangular, and multi-leg arbitrage.
Their longevity isn’t accidental. Years of consistent performance have earned them trust and deep industry connections with top-tier wallets, exchanges, mining pools, and hardware manufacturers.
Then come the opportunists—seasoned finance professionals who saw potential in crypto’s inefficiencies. Take Liu Zhen, founder of CCC, who spent years on Wall Street managing hedge funds before launching China’s first hedge fund in 2010. Or Song Zhengxin of Xique Finance, who managed $5 billion in quantitative assets at BlackRock with a 77% cumulative return over five years before entering crypto in 2017.
Their transition was natural. Traditional financial markets offer shrinking arbitrage opportunities, while crypto remains inefficient—much like early stock markets—making it fertile ground for quant strategies.
Finally, there are the pretenders: teams with glossy PPTs featuring “ex-Wall Street” experts and unverifiable performance charts promising 10% monthly returns. These outfits often lack real infrastructure or technical depth. As one insider put it: “You’re eyeing their returns; they’re eyeing your principal.”
Strategy Matters: CTA vs. Statistical Arbitrage
Two dominant strategies define the quant landscape: CTA (Commodity Trading Advisor) and statistical arbitrage.
CTA, or trend-following strategies, use time-series analysis to identify momentum. When prices trend upward, they buy; when they reverse, they sell low. High-risk and high-reward, these strategies depend heavily on accurate forecasting models.
More common is statistical arbitrage, which exploits temporary price discrepancies using algorithmic execution. This includes:
- Spot-spot arbitrage: Buying low on one exchange, selling high on another.
- Futures-spot (basis) arbitrage: Capitalizing on price gaps between spot and futures markets.
- Inter-futures arbitrage: Profiting from mispricing between different futures contracts.
- Triangular/multi-leg arbitrage: Looping through multiple assets or pairs to extract small spreads.
According to Yin Hongliang, arbitrage stabilizes markets by eliminating unfair pricing across platforms. “Returns are stable and uncorrelated with overall price direction,” he explains.
But here’s the catch: strategy homogenization is rampant. Most teams run similar models. The real edge lies in execution details—latency optimization, fee management, order routing precision.
“Small differences compound,” says a Hangzhou-based quant team. “At high frequency, a millisecond delay or inefficient slippage control can wipe out profits.”
Only elite teams focus purely on arbitrage. It requires deep financial engineering skills, robust infrastructure, and disciplined risk control—resources many so-called “quant” teams simply don’t have.
👉 See how algorithmic precision turns tiny spreads into consistent gains—no crystal ball needed.
Who’s Really Making Money?
Nearly every team we spoke with reported positive returns since inception.
Client-facing yields typically exceed 15% annualized, with some early entrants maintaining 50–60% yearly returns. A few claimed 150% annualized returns (in BTC terms) during peak volatility periods.
Collectively, these 20 teams manage an estimated 50,000 BTC—worth over $1.15 billion at current prices. At a conservative 15% return, that’s 7,500 BTC extracted annually from market inefficiencies.
Yet market volume tells a different story. Daily global crypto turnover has fallen below $120 billion—less than a third of its all-time high—and much of that is bot-generated wash trading.
“If you strip away the noise, real liquidity is thin,” says Li Zhe, partner at FutureMoney. “There are maybe a dozen serious teams transitioning from traditional finance. The rest? Noise.”
Li Zongcheng, CEO of Shicun Capital, puts it bluntly: “Quant trading is zero-sum—or worse, negative-sum after fees. For every winner, there’s a loser.”
With over 2,000 self-proclaimed quant teams in China alone, and only a fraction showing real results, the math doesn’t add up. Many are likely running Ponzi-like schemes disguised as algorithmic funds.
How to Spot a Fake Quant Team
So how do you tell the real players from the frauds?
1. Watch Out for Unrealistic Promises
Guaranteed 20% annual returns or “10% monthly” targets are red flags. High promised yields mean high funding costs—and higher pressure to take reckless risks.
2. Check Team Structure
Real quant teams don’t need traders staring at screens all day. If a team emphasizes manual monitoring or large operations staff, their strategy may be more trend-chasing than algorithmic.
3. Visit the Office
As Shi Ruoyang of Bemore suggests, physically visit the team. Real quant firms have server rooms, live dashboards showing live strategy performance, and technical staff actively refining models—not just salespeople pitching investors.
4. Avoid Cold Outreach
Legitimate quant teams rarely solicit funds publicly. Top performers often manage their own capital or accept only institutional money.
5. Never Hand Over Direct Control
Investors should never transfer funds directly to a team. Instead, grant API access to your exchange account—allowing trade execution but blocking withdrawals.
“Control your keys, control your risk,” says Song Zhengxin. “True quant is about trustless systems—not blind faith.”
Regulatory Clarity: The Missing Piece
China has taken a firm stance against crypto-related financial activities. Since 2017, ICOs and public fundraising for digital asset funds have been banned under anti-illegal fundraising regulations.
As Chen Yunfeng, senior partner at Zhonglun Wenden Law Firm notes, many so-called “quant funds” engaging in public fundraising may be violating laws against illegal deposit-taking or securities violations.
In response, some teams are going offshore:
- Liu Zhen’s fund operates under Hong Kong’s SFC regulatory framework, applying for a Type 9 Asset Management license.
- Others incorporate in the Cayman Islands and enforce strict KYC/AML checks to comply internationally.
- Several emphasize prior experience with FCA-regulated entities as proof of compliance readiness.
“We welcome regulation,” says Song Zhengxin. “It separates real builders from gamblers.”
The Road to Professionalization
Crypto quant trading remains immature compared to traditional finance. Infrastructure gaps persist in custody, reporting, and investor education.
Many teams lack formal training in risk modeling or statistical inference. When volatility spikes, poorly designed algorithms can fail catastrophically.
Meanwhile, investors often focus solely on returns—ignoring drawdowns, Sharpe ratios, or strategy transparency. This creates a classic adverse selection problem: bad actors thrive while disciplined teams struggle to attract capital.
Yet long-term outlooks remain optimistic.
“In traditional markets,” says Yin Hongliang, “50–85% of trading volume comes from quant strategies. Crypto will follow the same path.”
As liquidity improves and new capital enters during future bull runs, quant strategies will become standard tools for institutional-grade wealth management.
Weaker players will be culled. Profit margins will compress. But overall market efficiency—and fairness—will improve.
👉 Learn how the next generation of quant traders is reshaping crypto finance—legally and sustainably.
Frequently Asked Questions (FAQ)
Q: Is crypto quantitative trading still profitable in 2025?
A: Yes—but only for well-resourced teams with strong infrastructure and risk controls. Profitability now hinges on execution efficiency rather than simple strategy replication.
Q: What’s the average return for crypto quant funds?
A: Most legitimate funds target 15–30% annualized returns (in USD or stablecoins). Higher BTC-denominated returns often reflect market volatility rather than pure alpha.
Q: Can individuals run their own quant strategies?
A: Yes—with programming skills and access to APIs. However, retail traders face disadvantages in latency, data quality, and capital efficiency compared to institutional teams.
Q: Are most “quant funds” actually scams?
A: A significant portion operate with questionable transparency. Always verify team background, avoid guaranteed returns, and never hand over private keys.
Q: How does regulation affect crypto quant trading?
A: Increasingly strict rules in Hong Kong, Singapore, and Europe push legitimate operators toward compliance. Offshore registration and KYC enforcement are now standard among serious players.
Q: Will quant trading make crypto markets more stable?
A: Yes—by reducing price discrepancies across exchanges and dampening irrational swings through arbitrage and market-making activities.